An analytical approach to evaluate point cloud registration error utilizing targets

Point cloud registration is essential for processing terrestrial laser scanning (TLS) point cloud datasets. The registration precision directly influences and determines the practical usefulness of TLS surveys. However, in terms of target based registration, analytical point cloud registration error models employed by scanner manufactures are only suitable to evaluate target registration error, rather than point cloud registration error. This paper proposes an new analytical approach called the registration error (RE) model to directly evaluate point cloud registration error. We verify the proposed model by comparing RE and root mean square error (RMSE) for all points in three point clouds that are approximately equivalent

An Improved Passing Network for Evaluating Football Team Performance

With the continuous development of sensor technology, the realization of football techniques and tactics comes with richer technical support. Among them, network analysis has been widely used to analyze passing behavior, and some results have been achieved. However, most of these studies directly determine the weight of passing sidelines between players by measuring the number of passes, without carefully considering the potential contribution value of a single pass. In view of this problem, we carried out the following work: (1) map the football field to the coordinate system, calculate the endpoint coordinates of each pass, and take the coordinates as coefficients to obtain the weighted value of a single channel, and then calculate all channels together to achieve a directional channel network. (2) On this network, for the team evaluation that is difficult to quantify, we suggest that the ratio of the average clustering coefficient to the average intermediate centrality be taken as the overall network index to measure the coordination of the football team’s performance. (3) We tested the proposed index with two scores. The index passed the correlation and sensitivity tests, which proves that it is helpful for explaining the coordination level of the team and has certain reference value for the evaluation of the competitiveness of the football team

Establishment of a New Quantitative Evaluation Model of the Targets’ Geometry Distribution for Terrestrial Laser Scanning

The precision of target-based registration is related to the geometry distribution of targets, while the current method of setting the targets mainly depends on experience, and the impact is only evaluated qualitatively by the findings from empirical experiments and through simulations. In this paper, we propose a new quantitative evaluation model, which is comprised of the rotation dilution of precision ( r D O P , assessing the impact of targets’ geometry distribution on the rotation parameters) and the translation dilution of precision ( t D O P , assessing the impact of targets’ geometry distribution on the translation parameters). Here, the definitions and derivation of relevant formulas of the r D O P and t D O P are given, the experience conclusions are theoretically proven by the model of r D O P and t D O P , and an accurate method for determining the optimal placement location of targets and the scanner is proposed by calculating the minimum value of r D O P and t D O P . Furthermore, we can refer to the model ( r D O P and t D O P ) as a unified model of the geometric distribution evaluation model, which includes the D O P model in GPS

Life-cycle assessment of pyrolysis processes for sustainable production of biochar from agro-residues

Net carbon management of agro-residues has been an important pathway for reducing the environmental burdens of agricultural production. Converting agro-residues into biochar through pyrolysis is a prominent management strategy for achieving carbon neutrality in a circular economy, meeting both environmental and social concerns. Based on the latest studies, this study critically analyzes the life cycle assessment (LCA) of biochar production from different agro-residues and compares typical technologies for biochar production. Although a direct comparison of results is not always feasible due to different functional units and system boundaries, the net carbon sequestration potential of biochar technology is remarkably promising. By pyrolyzing agro-residues, biochar can be effectively produced and customized as: (i) alternative energy source, (ii) soil amendment, and (iii) activated carbon substitution. The combination of life cycle assessment and circular economy modelling is encouraged to achieve greener and sustainable biochar production

Combined Analysis with Copy Number Variation Identifies Risk Loci in Lung Cancer

Background. Lung cancer is the most important cause of cancer mortality worldwide, but the underlying mechanisms of this disease are not fully understood. Copy number variations (CNVs) are promising genetic variations to study because of their potential effects on cancer. Methodology/Principal Findings. Here we conducted a pilot study in which we systematically analyzed the association of CNVs in two lung cancer datasets: the Environment And Genetics in Lung cancer Etiology (EAGLE) and the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial datasets. We used a preestablished association method to test the datasets separately and conducted a combined analysis to test the association accordance between the two datasets. Finally, we identified 167 risk SNP loci and 22 CNVs associated with lung cancer and linked them with recombination hotspots. Functional annotation and biological relevance analyses implied that some of our predicted risk loci were supported by other studies and might be potential candidate loci for lung cancer studies. Conclusions/Significance. Our results further emphasized the importance of copy number variations in cancer and might be a valuable complement to current genome-wide association studies on cancer

Hybrid AI-assistive diagnostic model permits rapid TBS classification of cervical liquid-based thin-layer cell smears

Technical advancements have significantly improved early diagnosis of cervical cancer, but accurate diagnosis is still difficult due to various practical factors. Here, the authors develop an artificial intelligence assistive diagnostic solution to improve cervical liquid-based thin-layer cell smear diagnosis according to clinical TBS criteria in a large multicenter study